The present invention relates generally to computer processors, and more particularly, to a method, system, and storage medium for managing computer processor activities in a multi-processor computer environment
In a multi-processing computer system, multiple CPUs share various processing tasks requested by the operating system and applications executing on the system. Not all CPUs are equal in their ability to perform these tasks. Some processors are, by design, faster or more functional than others. Clearly, the costs of these processors increase in proportion to their speed and functionality. The processing needs and requirements of a system owner may vary over time or depending upon the types of functions to be performed on the system.
In contemporary computer networks, it is a common practice to interconnect multiple computing systems, typically called servers, in a manner that segregates each of the interconnected servers into separate usage classes based on the functions that each of these servers is configured to execute. For example, one or more of the interconnected servers may be assigned the task of executing application programs and others may be assigned the task of executing database programs that access and manage one or more of the network's associated databases. Networks that are structured in this manner are typically described as multiple-tier or multi-tier server networks.
The structuring of multi-tier networks and the assignment of work to each of the servers within the network is typically determined by a number of factors such as server reliability, server scalability, server functional capabilities, server cost, etc. Typically the computing functions that require the highest degrees of reliability, availability, scalability, and performance are assigned to the database servers that control the management and access of the network user's data. In other words, the core of many multi-tier computing networks, in terms of user data availability and reliability, lies at the data servers which are assigned the task of accessing, maintaining, and keeping up-to-date a centralized, integrated database upon which many companies rely for maintaining and growing their associated business. As such, the database servers are often the most reliable and functionally robust computing elements within the network and because of this are also quite often the most expensive servers within the network in terms of total “cost of ownership”.
Current and prior attempts to simplify and reduce the cost of multi-tier server networks by eliminating or minimizing the number of application servers and integrating the application programming functions onto combined application/database servers has had marginal success. This has typically been true because of the increased cost of ownership associated with the more robust database servers. Correspondingly, the proliferation of “dedicated” application servers within such networks is the current reality for many of today's network environments. While the initial cost to purchase and deploy additional application servers may be less than contemporary costs for integrating the application server's programming functions onto a large multi-function database server, such proliferation of these distributed application servers can typically increase the overall complexity and reduce the reliability of the network, and over time, can result in a greater total cost of ownership for the network in order to maintain the increased total number of server computing elements within the network.
Another factor which has resulted in significant increases in the number of dedicated application servers in contemporary multi-tier networks is the programming technologies currently being deployed in order to implement timely and cost effective applications. This is especially true for applications designed to support the evolving strategic e-business and on-demand business models. Programming languages such as JAVA and data structures such as XML, both of which play a major role in developing new strategic applications, provide significant advantages in terms of programming development costs and time to market, due to high level, application based, programming models they present to the program developer. Such high level programming languages are typically computer architecture agnostic in order to render the application programs operable on different hardware architecture server platforms. However, this “application can operate anywhere” design point has also resulted in significantly increasing the processing requirements of such applications in terms of actual processor instructions that must be executed in order to support a given application program. For example, new JAVA applications are emerging that can require the execution of as many as 75 million hardware instructions in order to process a single application transaction. Consequently, such applications are typically not cost effective when executed on more expensive database server platforms. The cost per unit of work is simply too great to deploy such applications on the typically more expensive, but highly reliable, database servers.
What is needed therefore is a way to consolidate the processing functions performed in a multi-processor computer environment.